Finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities
type: Item
instance of: scholarly article
title: Finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities
zbMATH Open document ID: 1474.34564
DOI: 10.1155/2014/597298
author: Li Liang
published in: Abstract and Applied Analysis
publication date: 2019-02-14T00:00:00Z
review text: Summary: This paper is concerned with the problem of finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities. By introducing the appropriate stochastic Lyapunov-Krasovskii functional and the concept of stochastically finite-time stochastic boundedness for Markovian jumping neural networks, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a prespecified finite-time interval. Finally, numerical examples are given to illustrate the effectiveness and reduced conservativeness of the proposed results.
Mathematics Subject Classification ID: 34K50
Mathematics Subject Classification ID: 34K12
Mathematics Subject Classification ID: 93E15
zbMATH DE Number: 7022687
Wikidata QID: Q59039797
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/597298
OpenAlex ID: W2033597981
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description: scientific article; zbMATH DE number 7022687